Overview

Dataset statistics

Number of variables10
Number of observations953
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory310.1 KiB
Average record size in memory333.3 B

Variable types

Text4
Numeric6

Alerts

released_year is highly overall correlated with in_spotify_playlistsHigh correlation
in_spotify_playlists is highly overall correlated with released_yearHigh correlation
track_id has unique valuesUnique
in_spotify_charts has 405 (42.5%) zerosZeros

Reproduction

Analysis started2024-06-26 16:55:30.614825
Analysis finished2024-06-26 16:55:34.799197
Duration4.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

track_id
Text

UNIQUE 

Distinct953
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2024-06-26T10:55:34.969447image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.996852
Min length4

Characters and Unicode

Total characters6668
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique953 ?
Unique (%)100.0%

Sample

1st row4082370
2nd row6247887
3rd row6974739
4th row2362023
5th row4386478
ValueCountFrequency (%)
4082370 1
 
0.1%
5374189 1
 
0.1%
3197174 1
 
0.1%
6974739 1
 
0.1%
2362023 1
 
0.1%
4386478 1
 
0.1%
5031502 1
 
0.1%
1892693 1
 
0.1%
7366228 1
 
0.1%
5563881 1
 
0.1%
Other values (943) 943
99.0%
2024-06-26T10:55:35.261436image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 752
11.3%
6 733
11.0%
2 716
10.7%
4 689
10.3%
1 689
10.3%
7 681
10.2%
5 673
10.1%
8 642
9.6%
0 551
8.3%
9 541
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6667
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 752
11.3%
6 733
11.0%
2 716
10.7%
4 689
10.3%
1 689
10.3%
7 681
10.2%
5 673
10.1%
8 642
9.6%
0 551
8.3%
9 541
8.1%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6668
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 752
11.3%
6 733
11.0%
2 716
10.7%
4 689
10.3%
1 689
10.3%
7 681
10.2%
5 673
10.1%
8 642
9.6%
0 551
8.3%
9 541
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 752
11.3%
6 733
11.0%
2 716
10.7%
4 689
10.3%
1 689
10.3%
7 681
10.2%
5 673
10.1%
8 642
9.6%
0 551
8.3%
9 541
8.1%
Distinct943
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size73.0 KiB
2024-06-26T10:55:35.495692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length123
Median length62
Mean length16.832109
Min length2

Characters and Unicode

Total characters16041
Distinct characters82
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique933 ?
Unique (%)97.9%

Sample

1st rowSeven (feat. Latto) (Explicit Ver.)
2nd rowLALA
3rd rowvampire
4th rowCruel Summer
5th rowWHERE SHE GOES
ValueCountFrequency (%)
95
 
3.2%
the 78
 
2.6%
feat 61
 
2.0%
with 46
 
1.5%
you 40
 
1.3%
me 39
 
1.3%
i 35
 
1.2%
a 26
 
0.9%
of 25
 
0.8%
love 24
 
0.8%
Other values (1499) 2530
84.4%
2024-06-26T10:55:35.838602image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2046
 
12.8%
e 1355
 
8.4%
o 910
 
5.7%
a 890
 
5.5%
i 796
 
5.0%
r 697
 
4.3%
t 665
 
4.1%
n 628
 
3.9%
s 536
 
3.3%
l 457
 
2.8%
Other values (72) 7061
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9563
59.6%
Uppercase Letter 3427
 
21.4%
Space Separator 2046
 
12.8%
Other Punctuation 280
 
1.7%
Other Symbol 179
 
1.1%
Open Punctuation 169
 
1.1%
Close Punctuation 160
 
1.0%
Decimal Number 139
 
0.9%
Dash Punctuation 75
 
0.5%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1355
14.2%
o 910
9.5%
a 890
 
9.3%
i 796
 
8.3%
r 697
 
7.3%
t 665
 
7.0%
n 628
 
6.6%
s 536
 
5.6%
l 457
 
4.8%
h 368
 
3.8%
Other values (16) 2261
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 300
 
8.8%
T 262
 
7.6%
A 250
 
7.3%
M 248
 
7.2%
L 211
 
6.2%
B 193
 
5.6%
I 164
 
4.8%
R 164
 
4.8%
C 158
 
4.6%
E 157
 
4.6%
Other values (16) 1320
38.5%
Other Punctuation
ValueCountFrequency (%)
. 105
37.5%
' 47
16.8%
& 35
 
12.5%
, 31
 
11.1%
: 18
 
6.4%
" 18
 
6.4%
! 12
 
4.3%
? 11
 
3.9%
/ 2
 
0.7%
# 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 36
25.9%
1 29
20.9%
0 23
16.5%
9 17
12.2%
5 16
11.5%
4 6
 
4.3%
3 5
 
3.6%
8 3
 
2.2%
6 3
 
2.2%
7 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 162
95.9%
[ 7
 
4.1%
Close Punctuation
ValueCountFrequency (%)
) 153
95.6%
] 7
 
4.4%
Math Symbol
ValueCountFrequency (%)
| 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
2046
100.0%
Other Symbol
ValueCountFrequency (%)
� 179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12990
81.0%
Common 3051
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1355
 
10.4%
o 910
 
7.0%
a 890
 
6.9%
i 796
 
6.1%
r 697
 
5.4%
t 665
 
5.1%
n 628
 
4.8%
s 536
 
4.1%
l 457
 
3.5%
h 368
 
2.8%
Other values (42) 5688
43.8%
Common
ValueCountFrequency (%)
2046
67.1%
� 179
 
5.9%
( 162
 
5.3%
) 153
 
5.0%
. 105
 
3.4%
- 75
 
2.5%
' 47
 
1.5%
2 36
 
1.2%
& 35
 
1.1%
, 31
 
1.0%
Other values (20) 182
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15862
98.9%
Specials 179
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2046
 
12.9%
e 1355
 
8.5%
o 910
 
5.7%
a 890
 
5.6%
i 796
 
5.0%
r 697
 
4.4%
t 665
 
4.2%
n 628
 
4.0%
s 536
 
3.4%
l 457
 
2.9%
Other values (71) 6882
43.4%
Specials
ValueCountFrequency (%)
� 179
100.0%
Distinct645
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Memory size71.6 KiB
2024-06-26T10:55:36.076372image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length117
Median length66
Mean length16.114376
Min length1

Characters and Unicode

Total characters15357
Distinct characters75
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique541 ?
Unique (%)56.8%

Sample

1st rowLatto, Jung Kook
2nd rowMyke Towers
3rd rowOlivia Rodrigo
4th rowTaylor Swift
5th rowBad Bunny
ValueCountFrequency (%)
the 66
 
2.5%
bad 41
 
1.6%
bunny 40
 
1.5%
taylor 38
 
1.5%
swift 38
 
1.5%
weeknd 37
 
1.4%
kendrick 23
 
0.9%
lamar 23
 
0.9%
sza 23
 
0.9%
lil 21
 
0.8%
Other values (1042) 2240
86.5%
2024-06-26T10:55:36.468585image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1639
 
10.7%
a 1339
 
8.7%
e 1196
 
7.8%
i 868
 
5.7%
n 836
 
5.4%
r 799
 
5.2%
o 730
 
4.8%
l 569
 
3.7%
, 529
 
3.4%
t 438
 
2.9%
Other values (65) 6414
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9945
64.8%
Uppercase Letter 3030
 
19.7%
Space Separator 1639
 
10.7%
Other Punctuation 569
 
3.7%
Other Symbol 91
 
0.6%
Decimal Number 59
 
0.4%
Dash Punctuation 15
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1339
13.5%
e 1196
12.0%
i 868
 
8.7%
n 836
 
8.4%
r 799
 
8.0%
o 730
 
7.3%
l 569
 
5.7%
t 438
 
4.4%
s 377
 
3.8%
u 360
 
3.6%
Other values (16) 2433
24.5%
Uppercase Letter
ValueCountFrequency (%)
S 297
 
9.8%
B 255
 
8.4%
T 228
 
7.5%
L 200
 
6.6%
M 197
 
6.5%
C 185
 
6.1%
D 167
 
5.5%
A 162
 
5.3%
K 128
 
4.2%
R 127
 
4.2%
Other values (16) 1084
35.8%
Decimal Number
ValueCountFrequency (%)
2 19
32.2%
1 15
25.4%
0 8
13.6%
4 6
 
10.2%
7 4
 
6.8%
5 3
 
5.1%
8 2
 
3.4%
3 1
 
1.7%
9 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 529
93.0%
. 18
 
3.2%
& 11
 
1.9%
! 5
 
0.9%
' 4
 
0.7%
* 1
 
0.2%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1639
100.0%
Other Symbol
ValueCountFrequency (%)
� 91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12975
84.5%
Common 2382
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1339
 
10.3%
e 1196
 
9.2%
i 868
 
6.7%
n 836
 
6.4%
r 799
 
6.2%
o 730
 
5.6%
l 569
 
4.4%
t 438
 
3.4%
s 377
 
2.9%
u 360
 
2.8%
Other values (42) 5463
42.1%
Common
ValueCountFrequency (%)
1639
68.8%
, 529
 
22.2%
� 91
 
3.8%
2 19
 
0.8%
. 18
 
0.8%
1 15
 
0.6%
- 15
 
0.6%
& 11
 
0.5%
0 8
 
0.3%
4 6
 
0.3%
Other values (13) 31
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15266
99.4%
Specials 91
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1639
 
10.7%
a 1339
 
8.8%
e 1196
 
7.8%
i 868
 
5.7%
n 836
 
5.5%
r 799
 
5.2%
o 730
 
4.8%
l 569
 
3.7%
, 529
 
3.5%
t 438
 
2.9%
Other values (64) 6323
41.4%
Specials
ValueCountFrequency (%)
� 91
100.0%

artist_count
Real number (ℝ)

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5561385
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:36.569361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.89304419
Coefficient of variation (CV)0.57388477
Kurtosis10.366704
Mean1.5561385
Median Absolute Deviation (MAD)0
Skewness2.5440322
Sum1483
Variance0.79752793
MonotonicityNot monotonic
2024-06-26T10:55:36.627928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 587
61.6%
2 254
26.7%
3 85
 
8.9%
4 15
 
1.6%
5 5
 
0.5%
6 3
 
0.3%
8 2
 
0.2%
7 2
 
0.2%
ValueCountFrequency (%)
1 587
61.6%
2 254
26.7%
3 85
 
8.9%
4 15
 
1.6%
5 5
 
0.5%
6 3
 
0.3%
7 2
 
0.2%
8 2
 
0.2%
ValueCountFrequency (%)
8 2
 
0.2%
7 2
 
0.2%
6 3
 
0.3%
5 5
 
0.5%
4 15
 
1.6%
3 85
 
8.9%
2 254
26.7%
1 587
61.6%

released_year
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.2382
Minimum1930
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:36.707339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1930
5-th percentile1999
Q12020
median2022
Q32022
95-th percentile2023
Maximum2023
Range93
Interquartile range (IQR)2

Descriptive statistics

Standard deviation11.116218
Coefficient of variation (CV)0.0055078821
Kurtosis20.513396
Mean2018.2382
Median Absolute Deviation (MAD)1
Skewness-4.2921176
Sum1923381
Variance123.5703
MonotonicityNot monotonic
2024-06-26T10:55:36.793314image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022 402
42.2%
2023 175
18.4%
2021 119
 
12.5%
2020 37
 
3.9%
2019 36
 
3.8%
2017 23
 
2.4%
2016 18
 
1.9%
2014 13
 
1.4%
2013 13
 
1.4%
2015 11
 
1.2%
Other values (40) 106
 
11.1%
ValueCountFrequency (%)
1930 1
 
0.1%
1942 1
 
0.1%
1946 1
 
0.1%
1950 1
 
0.1%
1952 1
 
0.1%
1957 2
0.2%
1958 3
0.3%
1959 2
0.2%
1963 3
0.3%
1968 1
 
0.1%
ValueCountFrequency (%)
2023 175
18.4%
2022 402
42.2%
2021 119
 
12.5%
2020 37
 
3.9%
2019 36
 
3.8%
2018 10
 
1.0%
2017 23
 
2.4%
2016 18
 
1.9%
2015 11
 
1.2%
2014 13
 
1.4%

released_month
Real number (ℝ)

Distinct12
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0335782
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:36.873343image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5664351
Coefficient of variation (CV)0.59109786
Kurtosis-1.1957936
Mean6.0335782
Median Absolute Deviation (MAD)3
Skewness0.18475844
Sum5750
Variance12.71946
MonotonicityNot monotonic
2024-06-26T10:55:37.141029image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 134
14.1%
5 128
13.4%
3 86
9.0%
6 86
9.0%
11 80
8.4%
12 75
7.9%
10 73
7.7%
4 66
6.9%
7 62
6.5%
2 61
6.4%
Other values (2) 102
10.7%
ValueCountFrequency (%)
1 134
14.1%
2 61
6.4%
3 86
9.0%
4 66
6.9%
5 128
13.4%
6 86
9.0%
7 62
6.5%
8 46
 
4.8%
9 56
5.9%
10 73
7.7%
ValueCountFrequency (%)
12 75
7.9%
11 80
8.4%
10 73
7.7%
9 56
5.9%
8 46
 
4.8%
7 62
6.5%
6 86
9.0%
5 128
13.4%
4 66
6.9%
3 86
9.0%

released_day
Real number (ℝ)

Distinct31
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.930745
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:37.209940image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median13
Q322
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.2019493
Coefficient of variation (CV)0.66054969
Kurtosis-1.2344145
Mean13.930745
Median Absolute Deviation (MAD)8
Skewness0.16410207
Sum13276
Variance84.675871
MonotonicityNot monotonic
2024-06-26T10:55:37.279697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 95
 
10.0%
21 44
 
4.6%
13 43
 
4.5%
24 40
 
4.2%
2 39
 
4.1%
20 39
 
4.1%
4 39
 
4.1%
7 39
 
4.1%
6 39
 
4.1%
10 37
 
3.9%
Other values (21) 499
52.4%
ValueCountFrequency (%)
1 95
10.0%
2 39
4.1%
3 32
 
3.4%
4 39
4.1%
5 25
 
2.6%
6 39
4.1%
7 39
4.1%
8 25
 
2.6%
9 36
 
3.8%
10 37
 
3.9%
ValueCountFrequency (%)
31 19
2.0%
30 22
2.3%
29 23
2.4%
28 21
2.2%
27 21
2.2%
26 13
 
1.4%
25 28
2.9%
24 40
4.2%
23 23
2.4%
22 33
3.5%

in_spotify_playlists
Real number (ℝ)

HIGH CORRELATION 

Distinct879
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5200.1249
Minimum31
Maximum52898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:37.353742image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile268.2
Q1875
median2224
Q35542
95-th percentile22267.4
Maximum52898
Range52867
Interquartile range (IQR)4667

Descriptive statistics

Standard deviation7897.609
Coefficient of variation (CV)1.5187345
Kurtosis9.8761188
Mean5200.1249
Median Absolute Deviation (MAD)1595
Skewness2.9291262
Sum4955719
Variance62372228
MonotonicityNot monotonic
2024-06-26T10:55:37.448410image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1150 3
 
0.3%
1112 3
 
0.3%
356 3
 
0.3%
86 3
 
0.3%
3006 3
 
0.3%
685 3
 
0.3%
896 3
 
0.3%
811 3
 
0.3%
1473 3
 
0.3%
892 3
 
0.3%
Other values (869) 923
96.9%
ValueCountFrequency (%)
31 1
 
0.1%
34 1
 
0.1%
58 1
 
0.1%
67 1
 
0.1%
77 1
 
0.1%
86 3
0.3%
99 1
 
0.1%
105 1
 
0.1%
130 1
 
0.1%
134 1
 
0.1%
ValueCountFrequency (%)
52898 1
0.1%
51979 1
0.1%
50887 1
0.1%
49991 1
0.1%
44927 1
0.1%
43899 1
0.1%
43257 1
0.1%
42798 1
0.1%
41751 1
0.1%
41231 1
0.1%

in_spotify_charts
Real number (ℝ)

ZEROS 

Distinct82
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.009444
Minimum0
Maximum147
Zeros405
Zeros (%)42.5%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-06-26T10:55:37.537766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile50
Maximum147
Range147
Interquartile range (IQR)16

Descriptive statistics

Standard deviation19.575992
Coefficient of variation (CV)1.6300498
Kurtosis8.5075814
Mean12.009444
Median Absolute Deviation (MAD)3
Skewness2.5804821
Sum11445
Variance383.21945
MonotonicityNot monotonic
2024-06-26T10:55:37.614535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 405
42.5%
4 48
 
5.0%
2 42
 
4.4%
6 36
 
3.8%
3 18
 
1.9%
8 17
 
1.8%
5 17
 
1.8%
1 16
 
1.7%
13 16
 
1.7%
12 16
 
1.7%
Other values (72) 322
33.8%
ValueCountFrequency (%)
0 405
42.5%
1 16
 
1.7%
2 42
 
4.4%
3 18
 
1.9%
4 48
 
5.0%
5 17
 
1.8%
6 36
 
3.8%
7 12
 
1.3%
8 17
 
1.8%
9 15
 
1.6%
ValueCountFrequency (%)
147 1
0.1%
130 1
0.1%
115 1
0.1%
113 1
0.1%
110 1
0.1%
104 1
0.1%
101 1
0.1%
100 1
0.1%
98 1
0.1%
91 1
0.1%
Distinct949
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size61.6 KiB
2024-06-26T10:55:37.811644image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length102
Median length9
Mean length9.09234
Min length4

Characters and Unicode

Total characters8665
Distinct characters41
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique945 ?
Unique (%)99.2%

Sample

1st row141381703
2nd row133716286
3rd row140003974
4th row800840817
5th row303236322
ValueCountFrequency (%)
723894473 2
 
0.2%
1223481149 2
 
0.2%
395591396 2
 
0.2%
156338624 2
 
0.2%
183706234 1
 
0.1%
505671438 1
 
0.1%
553634067 1
 
0.1%
95217315 1
 
0.1%
58149378 1
 
0.1%
725980112 1
 
0.1%
Other values (939) 939
98.5%
2024-06-26T10:55:38.092327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1082
12.5%
3 949
11.0%
2 879
10.1%
6 855
9.9%
4 822
9.5%
5 819
9.5%
7 816
9.4%
9 816
9.4%
8 786
9.1%
0 753
8.7%
Other values (31) 88
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8577
99.0%
Lowercase Letter 74
 
0.9%
Uppercase Letter 14
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
18.9%
s 10
13.5%
n 9
12.2%
a 5
 
6.8%
i 5
 
6.8%
c 5
 
6.8%
t 4
 
5.4%
l 3
 
4.1%
r 3
 
4.1%
y 3
 
4.1%
Other values (10) 13
17.6%
Uppercase Letter
ValueCountFrequency (%)
M 3
21.4%
A 2
14.3%
L 1
 
7.1%
I 1
 
7.1%
S 1
 
7.1%
E 1
 
7.1%
V 1
 
7.1%
D 1
 
7.1%
K 1
 
7.1%
P 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 1082
12.6%
3 949
11.1%
2 879
10.2%
6 855
10.0%
4 822
9.6%
5 819
9.5%
7 816
9.5%
9 816
9.5%
8 786
9.2%
0 753
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 8577
99.0%
Latin 88
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
15.9%
s 10
 
11.4%
n 9
 
10.2%
a 5
 
5.7%
i 5
 
5.7%
c 5
 
5.7%
t 4
 
4.5%
l 3
 
3.4%
r 3
 
3.4%
y 3
 
3.4%
Other values (21) 27
30.7%
Common
ValueCountFrequency (%)
1 1082
12.6%
3 949
11.1%
2 879
10.2%
6 855
10.0%
4 822
9.6%
5 819
9.5%
7 816
9.5%
9 816
9.5%
8 786
9.2%
0 753
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1082
12.5%
3 949
11.0%
2 879
10.1%
6 855
9.9%
4 822
9.5%
5 819
9.5%
7 816
9.4%
9 816
9.4%
8 786
9.1%
0 753
8.7%
Other values (31) 88
 
1.0%

Interactions

2024-06-26T10:55:34.097089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.128015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.846183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.366259image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.902418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.392560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.200261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.390767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.945389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.450680image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.985479image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.477446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.280652image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.478579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.028228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.577513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.063005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.554126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.359629image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.570977image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.105571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.652975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.142456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.652241image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.445874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.668534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.190089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.730040image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.220564image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.927809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.535308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:31.755474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.273917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:32.819946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:33.305377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2024-06-26T10:55:34.013240image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2024-06-26T10:55:38.187079image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
artist_countreleased_yearreleased_monthreleased_dayin_spotify_playlistsin_spotify_charts
artist_count1.0000.1950.033-0.001-0.1120.010
released_year0.1951.000-0.1240.108-0.6600.146
released_month0.033-0.1241.0000.104-0.041-0.031
released_day-0.0010.1080.1041.000-0.0370.025
in_spotify_playlists-0.112-0.660-0.041-0.0371.0000.128
in_spotify_charts0.0100.146-0.0310.0250.1281.000

Missing values

2024-06-26T10:55:34.643833image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-26T10:55:34.746224image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

track_idtrack_nameartists_nameartist_countreleased_yearreleased_monthreleased_dayin_spotify_playlistsin_spotify_chartsstreams
04082370Seven (feat. Latto) (Explicit Ver.)Latto, Jung Kook22023714553147141381703
16247887LALAMyke Towers12023323147448133716286
26974739vampireOlivia Rodrigo120236301397113140003974
32362023Cruel SummerTaylor Swift120198237858100800840817
44386478WHERE SHE GOESBad Bunny12023518313350303236322
55031502SprinterDave, Central Cee2202361218691183706234
61892693Ella Baila SolaEslabon Armado, Peso Pluma22023316309050725980112
77366228ColumbiaQuevedo12023777144358149378
85563881fukumeanGunna1202351510968395217315
95586506La Bebe - RemixPeso Pluma, Yng Lvcas22023317295344553634067
track_idtrack_nameartists_nameartist_countreleased_yearreleased_monthreleased_dayin_spotify_playlistsin_spotify_chartsstreams
9434322356Privileged RappersDrake, 21 Savage2202211410070112436403
9444343383The AstronautJin1202210284819203436468
9453108815BackOutsideBoyzDrake120221141045093367537
9468174233Broke BoysDrake, 21 Savage2202211410600106249219
9471587452The Great WarTaylor Swift12022102112740181382590
9483476877My Mind & MeSelena Gomez12022113953091473363
9492341529Bigger Than The Whole SkyTaylor Swift12022102111800121871870
9508553734A Veces (feat. Feid)Feid, Paulo Londra22022113573073513683
9516773043En La De EllaFeid, Sech, Jhayco32022102013200133895612
9526728037AloneBurna Boy12022114782296007391